The rapid advance of digital technology has created a great demand for, and corresponding advances in, wireless and wireline technology for communicating voice and data traffic. Much of this traffic is carried by the public switched telephone network over fiber optic cable and copper wire. Computers and other data equipment communicate over the Internet and a variety of proprietary local area networks (LANs) and wide area networks (WANs). Increasingly, various types of digital subscriber line (DSL) service or cable modem service are bringing broadband data into homes and offices. Many third generation cellular telephones and wireless PDA devices are also equipped to handle broadband data traffic and Internet capable.
However, even the most modern of wireless and wireline data communication equipment still must contend with age-old problems inherent in transmitting data through a channel from a transmitter to a receiver. Data is often transmitted as a series of pulses (or symbols) through a wire or the atmosphere. The data symbols may become distorted due to intersymbol interference (ISI), which is an overlap of adjacently transmitted symbols. In a wireless network, ISI may be caused by reflections of the transmitted symbols off natural objects (e.g., tress, hills) and man-made objects (e.g., buildings, brides) in the environment. The reflections cause multiple time-delayed, partially overlapping copies (echoes) of the same signal to arrive at the receiver. ISI also may occur in a non-linear, bandwidth limited channel if the symbol transmission rate is comparable to or exceeds the channel bandwidth, W.
Receivers frequently use a well-known technique, adaptive decision feedback equalization, to minimize the effects of ISI. An adaptive decision feedback equalizer (DFE) consists of a feedforward (or forward) filter, a feedback filter, and a decision circuit that decides or detects the value of each symbol in the received signal. The input to the forward filter is the received distorted sequence of data symbols. The input to the feedback filter is the sequence of previously decided (detected) symbols at the output of the decision circuit. The feedback filter removes from the symbol presently being estimated that portion of the ISI that is caused by previously detected symbols.
There are limitations, however, to the performance of decision feedback equalizers. Even under the best of circumstances, a DFE occasionally makes an incorrect decision regarding the value of a received data symbol. The incorrect estimate is then propagated back to the feedback filter, thereby affecting decisions regarding subsequent symbols. Furthermore, a DFE almost always does not perform detection on the first copy of a symbol as it is received. Because of the performance of the channel, symbol reflections may combine in such a way that the peak power of the transmitted symbol occurs after the first echo of the symbol enters the DFE. Thus, some reflections of a symbol (postcursors) are received by the DFE after a symbol is detected, but other reflections of a symbol (precursors) are received by the DFE before the symbol is due to be detected. A conventional DFE is unable to compensate for precursor ISI in the detection of the present symbol because of the causal nature of the feedback filter.
For example, in a sequence of ten symbols, the DFE may be working on detecting (deciding) the fifth symbol. However, precursor ISI from the sixth and seventh symbols and post-cursor ISI of the third and fourth symbols may contribute to distortion of the fifth symbol. Since the third and fourth symbols have already been decided by the decision circuit, the feedback loop can be used to remove the postcursor ISI. However, since the sixth symbol has not been detected yet, the feedback filter does nothing to remove the precursor ISI.
The performance of a DFE also is affected by the type of data on which the receiver operates. In digital television and radio systems, a continuous stream of incoming data symbols must be processed in real time. This places a practical limit on the amount of signal processing that can occur during the detection of symbols. In a real time system, the DFE can only operate on a relatively small window of symbols in an infinite stream of incoming symbols. The real time system cannot account for long delayed ISI from other data symbols outside the window of symbols being processed.
Other types of systems, however, have better performance because data symbols are received in finite-sized data blocks that may be repeatedly analyzed “offline,” rather than in real time, by a DFE, including a block DFE specifically designed to operate on fixed-size data blocks. For example, data symbols are transmitted in fixed-size data packets on the Internet and different types of LAN and WAN networks. A network or Internet receiver can signal process the fixed-size data packet offline and simultaneously determine all of the symbols in the data packet. Because the packet size is known and there are transmission delays between data packets, all ISI (precursor and postcursor) affecting the symbols in a data packet are due to other data symbols in the same data packet. This property permits more reliable detection of data symbols. The performance of the receiver is further enhanced by inserting blocks of known symbols in an optimal manner in the unknown symbols generated by a user application. Known symbols are primarily introduced for purposes such as channel estimation, synchronization, or the like, but known symbols can also be used to improve detection by reducing the ISI in the data block.
Some real time communication systems also transmit data symbols in fixed size data packets that include known and unknown symbols. If the symbol rate of such a real-time communication system is relatively low, such as in a Global System for Mobile (GSM) network, the same benefits may be realized because there is sufficient time between data packets to permit analysis of the entire data packet simultaneously. Nonetheless, even with fixed-size data packets, conventional DFEs and block DFEs occasionally makes an incorrect decision regarding the value of a received data symbol.
There is therefore a need in the art for improved receivers and transmitters for use in communication networks. In particular, there is a need in the art for improved decision feedback equalizers that have a lower detected symbol error rate. More particularly, there is a need for improved transmitters and data networks that are capable of maximizing the performance of receivers that contain decision feedback equalizers that operate on fixed-size data packets.